#164: How Automation and Data Simplification can Empower Non-Technical Merchants

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Claus Lauter: Hello, and welcome to another episode of the E-Commerce Coffee Break podcast. Today we want to talk about a topic that a lot of merchants have to battle with, and that's too much data from too many sources. Now, in the past episode, we talked a lot about why good data is so important, but in the day-to-day business, specifically non-technical merchants struggle to get all the data into one place and to read out the data in the best way possible.

Now, this cost usually a lot of time, and there's about 2 million e-commerce stores alone on Shopify. it's very difficult for most merchants to make quick decisions on their business because they're obviously not data analysts there. So that's a topic we wanna talk about today and with me on the show.

I have Saptarshi Nath with me. He is the founder of air boxer.com and he's a seasoned entrepreneur with the background in [00:02:00] venture capital management consulting. He has a successful. Record of building D2C brands that attracted over 2 million monthly visitors and generated around 10 million in annual sales.

He's not a stranger to the business world. He also worked extensively on data studies for Fortune 100 companies and advised deep tech founders in launching their business in various industries. So let's welcome Saptarshi. Hey, how are you today? Thank

Saptarshi Nath: you for having me Claus. Glad to be.

Claus Lauter: You're welcome.

Let's dive into how to make data easier to read for merchants. So what's the biggest struggle that you see , for merchants when it comes to getting all the bits and pieces together to get good results from their data?

Saptarshi Nath: Yeah, that's a good point. Mainly the reason why we created Air Boxer in the first place.

But generally, if you look at, a business organization, even if it's a small team of 10 people running a d d C company, you'll find there are these people who are the business people who are making decisions around sales, who are making decisions around marketing, budgeting, things like that.

And, If you're lucky, you have someone who [00:03:00] is more of a data analyst, kind of a profile who knows how to pull data from different data sources and all that. But, , most people don't have access to an analyst profile inside of their company. It's definitely not in the earlier days of the company.

you can't really expect a business person to know how to query databases or even how to set up databases , and this was a bit surprising, , to us as well. Even being able to ask the right question in the first. So when you've just launched a new brand, , unless you've, launched 15 brands before, , if you're just starting out, you'll find that, what are the different metrics I should be tracking?

How do I get to know who my most valuable customers are? These seem like basic questions, but, pulling the data to answer those questions behind the scenes is actually quite a few steps, , in there. In my mind, based on what I've seen myself and what I've heard from our users, , they don't really mind looking at data, what they mind is.

, pulling, , exporting C s V files, cleaning the data so they can talk to each other. Pulling data from five different sources, putting them together, creating a report, , for [00:04:00] their management, only for it to be outdated three days later, and they have to do this all over again. .

Claus Lauter: Yeah, very good point.

And I think time is crucial for most merchants, specifically when they're startups or solopreneurs. , they're all over the place. They have to deal with so many different things. And they said it's difficult to find or to know the right KPIs. And then you have these different tools. You have the Shopify dashboard, you have, , Google Analytics, and so on, so forth.

And you end up pulling the data there, as I said, , in CSV files. And then you need to start. Getting this data together in a readable format. So that's very, very difficult. , you have developed something that makes it easier and I had a look at it and I think it's, quite a good thing. , I should have had that six years ago when I started my Shopify store.

So gimme a bit of an overview on how you approach this kind of, , challenge.

Saptarshi Nath: so we are a lot more prescriptive than, , other, , data analytics tools we're targeted at a business leader, someone like a marketing manager or a, director or category manager and such. , , one of our core philosophies is that you should be doing, whatever your role is and not [00:05:00] focus on, , creating, something from scratch, If a new store, , launches on Shopify today, they're following what? 18 years of, what other companies have done before, almost everyone that, , runs a Shopify store also runs ads on Google and Facebook. Maybe now TikTok as long as more people have come before you doing the same thing, why should you have to, reinvent the wheel?

Why should you have to create your own way of doing things, creating your own reports? So what we have done is we've taken the best, , learnings from all the merchants. We work with everyone, all the d d C brands in our network for now there are. Just under 60, , automations, , that help you answer a very specific question or they help you create a report to get a business, , health check.

What you've done is, okay, you just started a new Shopify store, noit to, , try and, , solve all of data analysis and all of reporting for yourself. Just click this button and this will be done for. , and literally for most, , analysis, it is one or two clicks that gives you a report, that gives you, all the [00:06:00] metrics that you need to look at.

One thing that we have, , done, , slightly differently from others is that we do not compete with spreadsheets because we know that people love spreadsheets, whether they admitted or not. Eventually, the data they look at is going to end up in a spreadsheet somewhere. So what we have done is, , we say that, Hey, you already create your reports on spreadsheets.

We know that. So we want, , ask you to move to our platform or do something drastically different. we will create the reports and send them to the spreadsheets that you already use. So we will embed into your existing workflow instead of trying to force you to, work in our way.

, the other thing that we do apart from reporting is that, this is, slightly more important for founders and, , people who make revenue calls generally. , where we pull, , just in time data from your Shopify store and your other ad channels to tell you when something needs attention. For example, your, , hot selling item suddenly has shown a lot of, , abandoned cards, right?

, you won't be, preemptively tracking that, but we do, and we will [00:07:00] send it to your dashboard saying, Hey, this product, usually sells really well, but it's seen 90 abandoned cards in the last three days. Do you wanna check it out? Something could be going wrong. , and in those cases, , you don't really need to think about.

What question to ask, how do I pull this data? How do I find out what my abandoned cart rate for a specific hot selling product is? All of that happens, , automatically behind the scenes.

Claus Lauter: Okay. , I like that you're pulling it directly into a spreadsheet, and I think it works quite nicely with Google spreadsheets there as well, Correct me if I'm wrong, but also , with your app, , the risk that something breaks is less because usually if you do this things manually, , any supplier out there clavio Facebook, they're changing their platforms. So that Means that something can break and you do need to even know about it, and then you start from scratch, as you said, when we are looking into these different automations that you have, give me just, , three, four examples , on different aspects.

So for marketing, for finance, whatever, so that our business get an idea what they

Saptarshi Nath: can do

[00:08:00]

Saptarshi Nath: , The example I cited earlier on, like if you want to know who your most valuable customers are, in retail, there's usually this, , concept of A R F M analysis, which is basically, you rank your customers by how often they order, when was the last time they ordered, and how much money they spend with you Now trying to do that, you normally have to download your entire list of, customers from Shopify [00:09:00] again, find out when was the last time they ordered, what was the total amount of money they spent with you and so on.

, and then. Organize them into quintiles, give them a score from one to five, and then rank them again, based on those scores. So obviously this is something as you can, imagine, take some time to put together. Now, this is one of the automations that we have where you literally just click a button behind the scenes.

We will pull the data, we will do , the allocation of scores to each customer, and then you'll tell you that, okay, these are the ones who are your most valuable customers. Then you can, download the sheet or CSV file and then upload it to Clearview. To say, create a new segment of my most valuable customers.

in the future, we're looking at a way where we can just send it Tola view ourselves, but for now we are just displaying it to you in your spreadsheet. , before I get to marketing, let's say on the ops side, you want to know which of your shipping carriers is, delivering on time, which ones are behind schedule, right?

, so does FedEx work great or do you want to use, , someone else? This is something that, you click a single button and it gives you, , how many on-time deliveries happened, how many deliveries happened within 24 [00:10:00] hours, 48 hours, 72 hours arranged by each of your shipping partners.

, and for most, Entrepreneurs. I think this is data that they want to have at their fingertips, but not something they're willing to spend five days to go and pull from, raw data. and on the marketing side, there are some very common reports like which campaigns are working best.

What kind of keywords do I rank better for? , those kind of, , reporting metrics are, different, , hops that can be used. By hops, I mean automat. .

Claus Lauter: Now you have these, , pre-formulated hops, can merchants also create their own hops in your system?

Saptarshi Nath: That is a good point, and there is a good story story behind this as well.

We actually started out as a Google sheet, extension. , and that extension had a very comprehensive, query builder where you could literally pull together a lot of, variables from different places. Identify it in this way. I wanna aggregate it in that way and then get a result, right.

I'd say less than 20% of the people created a query from scratch. Instead, we had some pre-built queries in there, people who just used the pre-built [00:11:00] queries. When we built this platform, we decided, hey, let us start from the other direction. Let's give them the queries. Let's not provide, , a full, , query builder, , that gives that overwhelm.

In the product that we have now, , you can't create, an automation from scratch, but using one of our existing automations, , you can, , modify it. , for example, you want, , only customers who have spent more than f. $5,000 in the last 12 months. , you can add it as a filter.

Give me only the list of, customers who have spent more than $5,000. , and you can change things like timeframes. Say I want this for the last seven days, months to date last three months. , you could make those changes, but you will always have to start with an automation that already.

Claus Lauter: Okay. No, makes perfect sense because we're talking you about people who are not technical, who are not data analysts, or to make it as easy as possible. When it comes to scheduling your reporting, how does that work?

Saptarshi Nath: That is actually quite simple. , once you have set up the report that you want, you know that this is the, , automation that's giving me, , what I want.

, [00:12:00] there's simply a schedule button. You click that button and you , tell the, platform. How often do you want this report to run? Like once a day, morning mo, Monday morning at 8:00 AM. Or once in seven days, however you want to set it up, that schedule will be, , set and then it'll keep on running behind the scenes.

So if you use it only for automating an existing report, you don't even need to log into the platform. It'll keep on running, , behind the scenes.

Claus Lauter: Okay. And your data, then you get an email or how do you get informed when a new report is is ready? ,

Saptarshi Nath: Every time the report is ready, , you'll be sent, , a notification saying that, this report has run successfully.

Click here to open the report.

Claus Lauter: Okay. Let's take , a step back and let me know. Obviously working with a lot of Mauritians, what are the most common automations they're going for when they start with your system?

Saptarshi Nath: the most common one that almost everyone starts with is a business health metric, which is set of business health metrics, which are, , arranged by dates.

So every day I want to know what my total sales were, what my returns were, how much did I spend on, , [00:13:00] how much did I charge for shipping? How much did I spend on advertising? , how much returns did I refunds, did I send back, , everything arranged on it, , daily basis. , some of our users, they use that automation to see the data and , like on their spreadsheets.

So it basically gives you. Everything you need to know about your business in one view. , some users, , hook it up to Google Data Studio behind the scenes so that apart from having a spreadsheet, they also have a dashboard that, , gives them like a few nice looking, , charts and graphs.

Claus Lauter: Okay. Well that sounds great. Now, when it comes to implementation, is there any kind of homework that a merchant needs to do before they get started?

Saptarshi Nath: Because we have a very tight integration on Google Sheets, you need to have a Google account, , to even create an account.

, it can be a , G-suite. Workspace account, or it can be a Gmail account as well. If your business is not on, , Google, then you can use a Gmail account as well. , you just log in with Google to create an account. Then you log into Shopify to connect your Shopify, , install our Shopify app to connect to Shopify, connect to Facebook, to log into Google Analytics.

It's only. Clavio that they need to [00:14:00] copy and paste the code from Clavio into air boxer. But otherwise, the rest of them are simply just logging into that portal.

Claus Lauter: Okay, that sounds very straightforward. Now tell me a little bit about the pricing structure of Air

Saptarshi Nath: Boxer. like most companies we're also playing around with our pricing, , and it is the best practice to be playing around with the pricing every quarter or so.

But, right now we, have only two plans. , one is a $50 plan for personal, as in which doesn't have any team features and $150 plan, which has a team feature on it,

Claus Lauter: okay. I think a team feature for bigger enterprise is definitely something that's very important cuz then you have your different departments accessing different hops and, and working from there.

I think the solution is, quite easy and straightforward. So I said I had a look at it and I really like it. I'm not a numbers person so , I'm not a biggest fan of spreadsheets, but, , seeing what you have there I think definitely makes one's lives easier. So thanks so much. , where can people find out more about,

Saptarshi Nath: The website is called air boxer.com.

, it's spelled airbox, A I R B O x, then r , dot com. , [00:15:00] everything you need to know will be on there. You can also find me on LinkedIn. My full name is Subter, so search using Subter space. Nath, n et h. and you should be able to find me on Twitter also. I am again, DM me or ping me on there. My dms are also open.

Claus Lauter: Excellent. I will put the links in the show notes. Then you just won't click away. Thanks so much for your time. I think it was a very good overview of io, I think is a very helpful app for most merchants and thanks

Saptarshi Nath: for your time. Thank you so much Claus for having me. Bye-Bye.